Evidence map›Paper›PMID 36100821›Full record

ArticleMemory & cognition2023

Long-term memory representations for audio-visual scenes.

Hauke S Meyerhoff, Oliver Jaggy, Frank Papenmeier, Markus Huff

Abstract read
In one paragraph

Article in Memory & cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hauke S MeyerhoffUniversity of Erfurt, Nordhäuser Str. 63, 99089, Erfurt, Germany. hauke.meyerhoff@uni-erfurt.de.ORCID 0000-0003-1836-4737
Oliver JaggyLeibniz-Institut für Wissensmedien, Tübingen, Germany.
Frank PapenmeierDepartment of Psychology, University of Tübingen, Tübingen, Germany.
Markus HuffLeibniz-Institut für Wissensmedien, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we investigated the nature of long-term memory representations for naturalistic audio-visual scenes. Whereas previous research has shown that audio-visual scenes are recognized more accurately than their unimodal counterparts, it remains unclear whether this benefit stems from audio-visually integrated long-term memory representations or a summation of independent retrieval cues. We tested two predictions for audio-visually integrated memory representations. First, we used a modeling approach to test whether recognition performance for audio-visual scenes is more accurate than would be expected from independent retrieval cues. This analysis shows that audio-visual integration is not necessary to explain the benefit of audio-visual scenes relative to purely auditory or purely visual scenes. Second, we report a series of experiments investigating the occurrence of study-test congruency effects for unimodal and audio-visual scenes. Most importantly, visually encoded information was immune to additional auditory information presented during testing, whereas auditory encoded information was susceptible to additional visual information presented during testing. This renders a true integration of visual and auditory information in long-term memory representations unlikely. In sum, our results instead provide evidence for visual dominance in long-term memory. Whereas associative auditory information is capable of enhancing memory performance, the long-term memory representations appear to be primarily visual.

Indexed as

Memory, Long-TermVisual PerceptionCognitionCuesHumansRecognition, PsychologyAudio-visual advantageAudio-visual integrationLong-term memoryNaturalistic scenesStudy-test congruency

Identifiers

PMID36100821
PMCPMC9950240

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.